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Personalized Digital Television pp 73–91Cite as

Interactive Television Personalization

From Guides to Programs

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Part of the book series: Human-Computer Interaction Series ((HCIS,volume 6))

Abstract

The personalized Electronic Program Guide (pEPG) has been touted as a possible solution to the information overload problem faced by Digital TV (DTV) users. It leverages artificial intelligence and user profiling techniques to learn about the viewing preferences of individual users in order to compile viewing guides that fit their individual preferences. In this chapter, we focus on the recommendation technology used by existing pEPG’s and argue that certain important shortcomings (related to profile sparsity and recommendation diversity) exist that impact the future success of pEPG’s. We describe how data mining approaches can be used to alleviate many of these problems and present results of a comprehensive evaluation of such approaches.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University College Dublin, Dublin, 4, Ireland

    Derry O’Sullivan & Barry Smyth

  2. Department of Software & Information Systems, University of North Carolina at Charlotte, USA

    David Wilson

  3. Centre for Digital Video Processing, Dublin City University, Dublin, 9, Ireland

    Kieran Mc Donald & Alan F. Smeaton

Authors
  1. Derry O’Sullivan
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  2. Barry Smyth
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  3. David Wilson
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  4. Kieran Mc Donald
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  5. Alan F. Smeaton
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© 2004 Kluwer Academic Publishers

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O’Sullivan, D., Smyth, B., Wilson, D., Mc Donald, K., Smeaton, A.F. (2004). Interactive Television Personalization. In: Personalized Digital Television. Human-Computer Interaction Series, vol 6. Springer, Dordrecht. https://doi.org/10.1007/1-4020-2164-X_4

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  • DOI: https://doi.org/10.1007/1-4020-2164-X_4

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-2163-3

  • Online ISBN: 978-1-4020-2164-0

  • eBook Packages: Springer Book Archive

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